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Neural networks for large financial crashes forecast

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  • Rotundo, G.

Abstract

The aim of this work is to examine how neural networks can be used for solving the problem of the forecast of large financial crashes due to the presence of speculative bubbles. Some microeconomic theories have been developed for the explanation of a bubble due to a cooperation among the investors. This behaviour can be detected by the presence of self-similarity in the indexes series near the crash time leading to a differential equation and thus to a dynamical system description, well suitable by a neural network approach.

Suggested Citation

  • Rotundo, G., 2004. "Neural networks for large financial crashes forecast," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(1), pages 77-80.
    • Handle: RePEc:eee:phsmap:v:344:y:2004:i:1:p:77-80
    DOI: 10.1016/j.physa.2004.06.091
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    References listed on IDEAS

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    1. Alain Arneodo & Jean-Philippe Bouchaud & Rama Cont & Jean-Francois Muzy & Marc Potters & Didier Sornette, 1996. "Comment on "Turbulent cascades in foreign exchange markets"," Science & Finance (CFM) working paper archive 9607120, Science & Finance, Capital Fund Management.
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    Cited by:

    1. Raquel M. Gaspar & Sara D. Lopes & Bernardo Sequeira, 2020. "Neural Network Pricing of American Put Options," Risks, MDPI, vol. 8(3), pages 1-24, July.
    2. Angelini, Eliana & di Tollo, Giacomo & Roli, Andrea, 2008. "A neural network approach for credit risk evaluation," The Quarterly Review of Economics and Finance, Elsevier, vol. 48(4), pages 733-755, November.
    3. Ali Asgary & Ali Sadeghi Naini, 2011. "Modelling The Adaptation Of Business Continuity Planning By Businesses Using Neural Networks," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 18(2-3), pages 89-104, April.
    4. Lahmiri, Salim, 2016. "Interest rate next-day variation prediction based on hybrid feedforward neural network, particle swarm optimization, and multiresolution techniques," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 388-396.

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    Keywords

    Large financial crashes; Neural networks;

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